Details
Original language | English |
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Title of host publication | Informatics in Contrl, Automation and Robotics |
Editors | K. Madani, D. Peaucelle, O. Gusikhin |
Publisher | Springer Nature |
Pages | 367-384 |
Publication status | Published - 2017 |
Abstract
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Informatics in Contrl, Automation and Robotics. ed. / K. Madani; D. Peaucelle; O. Gusikhin. Springer Nature, 2017. p. 367-384.
Research output: Chapter in book/report/conference proceeding › Contribution to book/anthology › Research › peer review
}
TY - CHAP
T1 - A Comparison of Discretization Methods for Parameter Estimation of Nonlinear Mechanical Systems Using Extended Kalman Filter: Symplectic vs. Classical Approaches
AU - Beckmann, D.
AU - Dagen, M.
AU - Ortmaier, T.
PY - 2017
Y1 - 2017
N2 - This paper presents two symplectic discretization methods in the context of online parameter estimation for nonlinear mechanical systems. The symplectic approaches are compared to established discretization methods (e.g. Euler Forward and Runge Kutta) regarding accuracy and computational effort. The methods are compared using two mechanical simulation models of a real belt-drive system: a nonlinear two-mass system with two degrees of freedom and a nonlinear three-mass system with three degrees of freedom. In addition, the influence of the discretization method on the performance of an augmented Extended Kalman Filter (EKF) estimating the parameter of the two-mass system is analyzed. The simulation shows improved accuracy of the calculated discrete-time solution using symplectic integrators in comparison to the conventional methods, with almost the same or lower computational cost. Additionally, the parameter estimation based on the EKF in combination with the symplectic integration scheme leads to more accurate values.
AB - This paper presents two symplectic discretization methods in the context of online parameter estimation for nonlinear mechanical systems. The symplectic approaches are compared to established discretization methods (e.g. Euler Forward and Runge Kutta) regarding accuracy and computational effort. The methods are compared using two mechanical simulation models of a real belt-drive system: a nonlinear two-mass system with two degrees of freedom and a nonlinear three-mass system with three degrees of freedom. In addition, the influence of the discretization method on the performance of an augmented Extended Kalman Filter (EKF) estimating the parameter of the two-mass system is analyzed. The simulation shows improved accuracy of the calculated discrete-time solution using symplectic integrators in comparison to the conventional methods, with almost the same or lower computational cost. Additionally, the parameter estimation based on the EKF in combination with the symplectic integration scheme leads to more accurate values.
M3 - Contribution to book/anthology
SP - 367
EP - 384
BT - Informatics in Contrl, Automation and Robotics
A2 - Madani, K.
A2 - Peaucelle, D.
A2 - Gusikhin, O.
PB - Springer Nature
ER -